Functions — github.com/CommissarMa/CSRNet-pytorch

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Functions22 in github.com/CommissarMa/CSRNet-pytorch

⨍ Functions 22 ◇ Types & classes 5

↓ 2 callersFunctionmake_layers

(cfg, in_channels=3, batch_norm=False, dilation=False)

↓ 1 callersMethod__mkdir

create directory while not exist

↓ 1 callersMethod_initialize_weights

↓ 1 callersFunctioncal_mae

Calculate the MAE of the test data. img_root: the root of test image data. gt_dmap_root: the root of test ground truth density-map data.

↓ 1 callersFunctioncreate_test_dataloader

Create train dataloader. root: the dataset root.

↓ 1 callersFunctioncreate_train_dataloader

Create train dataloader. root: the dataset root. use_flip: True or false. batch size: the batch size.

↓ 1 callersFunctiondenormalize

↓ 1 callersFunctiongenerate_fixed_kernel_densitymap

Use fixed size kernel to construct the ground truth density map for ShanghaiTech PartB. image: the image with type numpy.ndarray and [h

data_preparation/dmap_for_SHHB.py:14

↓ 1 callersFunctiongenerate_k_nearest_kernel_densitymap

Use k nearest kernel to construct the ground truth density map for ShanghaiTech PartA. image: the image with type numpy.ndarray and [he

data_preparation/dmap_for_SHHA.py:20

↓ 1 callersFunctiongenerate_perspective_densitymap

Use perspective kernel to generate density map. image: the image. points: n points with [col, row] p_map: perspective map.

data_preparation/dmap_for_MALL.py:10

↓ 1 callersMethodget_params

↓ 1 callersMethodread_image_and_dmap

img: PIL.Image dmap: PIL.Image

img: PIL.Image dmap: PIL.Image

Method__getitem__

root: the root path of dataset. phase: train or test. main_transform: transforms on both image and density map. img_t

(self, factor=16)

(self, load_weights=False)

Functionestimate_density_map

Show one estimated density-map. img_root: the root of test image data. gt_dmap_root: the root of test ground truth density-map data.